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Volumn 2, Issue , 2004, Pages 1375-1380

An input variable importance definition based on empirical data probability and its use in variable selection

Author keywords

[No Author keywords available]

Indexed keywords

DATASETS; FEATURE SELECTION; NON-LINEAR MODELS; SUBSETS;

EID: 10944225915     PISSN: 10987576     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IJCNN.2004.1380149     Document Type: Conference Paper
Times cited : (5)

References (11)
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    • Bootstrapping confidence intervals for clinical inputs variable effects in a network trained to identify the presence of acute myocardial infraction
    • W. G. Baxt and H. White. Bootstrapping confidence intervals for clinical inputs variable effects in a network trained to identify the presence of acute myocardial infraction. Neural Computation, 7:624-638, 1995.
    • (1995) Neural Computation , vol.7 , pp. 624-638
    • Baxt, W.G.1    White, H.2
  • 2
    • 0031334221 scopus 로고    scopus 로고
    • Selection of relevant features and examples in machine learning
    • December
    • A. Blum and P. Langley. Selection of relevant features and examples in machine learning. Artificial Intelligence, 97(1-2):245-271, December 1997.
    • (1997) Artificial Intelligence , vol.97 , Issue.1-2 , pp. 245-271
    • Blum, A.1    Langley, P.2
  • 4
    • 0008642385 scopus 로고
    • Refined pruning techniques for feed-forward neural networks
    • Anthony N. Burkitt. Refined pruning techniques for feed-forward neural networks. Complex System, 1992.
    • (1992) Complex System
    • Burkitt, A.N.1
  • 5
    • 0036193080 scopus 로고    scopus 로고
    • A methodology to explain neural network classification
    • Raphael Féraud and Fabrice Clérot. A methodology to explain neural network classification. Neural Networks, 15:237-246, 2002.
    • (2002) Neural Networks , vol.15 , pp. 237-246
    • Féraud, R.1    Clérot, F.2
  • 6
    • 33745561205 scopus 로고    scopus 로고
    • An introduction to variable and feature selection
    • Isabelle Guyon and André Elisseef. An introduction to variable and feature selection. JMLR, 3(Mar):1157-1182, 2003.
    • (2003) JMLR , vol.3 , Issue.MAR , pp. 1157-1182
    • Guyon, I.1    Elisseef, A.2
  • 7
    • 10944266545 scopus 로고    scopus 로고
    • JMLR special issue on variable and feature selection
    • JMLR, editor
    • JMLR, editor. JMLR Special Issue on Variable and Feature Selection, volume 3(Mar). Journal of Machine Learning Research, 2003.
    • (2003) Journal of Machine Learning Research , vol.3 , Issue.MAR
  • 8
    • 0031381525 scopus 로고    scopus 로고
    • Wrappers for feature subset selection
    • R. Kohavi and G. John. Wrappers for feature subset selection. Artificial Intelligence, 97(1-2), 1997.
    • (1997) Artificial Intelligence , vol.97 , Issue.1-2
    • Kohavi, R.1    John, G.2
  • 10
    • 0028277023 scopus 로고
    • Stock performance using neural networks: A comparative study with regression models
    • A. N. Réfénes, A. Zapranis, and J. Utans. Stock performance using neural networks: A comparative study with regression models. Neural Network, 7:375-388, 1994.
    • (1994) Neural Network , vol.7 , pp. 375-388
    • Réfénes, A.N.1    Zapranis, A.2    Utans, J.3
  • 11
    • 10944252019 scopus 로고    scopus 로고
    • SCAAT: Incremental tracking with incomplete information
    • Los Angeles, August 12-17
    • Greg Welch and Gary Bishop. SCAAT: Incremental tracking with incomplete information. In SIGGRAPH, Los Angeles, August 12-17 2001.
    • (2001) SIGGRAPH
    • Welch, G.1    Bishop, G.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.